Quantum-Inspired Data Structures for Parallel Computing

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum-inspired data structures offer a novel approach to parallel computing by utilizing the principles of quantum mechanics, particularly superposition and entanglement, to optimize the execution of computational tasks. This paper investigates the design and potential benefits of such data structures, aiming to achieve exponential speedups in certain computational scenarios. The core claim is that these data structures can significantly enhance the efficiency of parallel computations through a fundamentally different algorithmic approach. We explore the mathematical underpinnings of these structures and present preliminary results demonstrating their potential to outperform existing classical data structures under specific conditions. This work represents a significant step towards harnessing the power of quantum phenomena for parallel processing, offering a potentially transformative paradigm in computational efficiency.

DOI: 10.5281/zenodo.22589678

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